Sub-perception calibration using time domain scaling

ABSTRACT

An example of a system to program a neuromodulator to deliver neuromodulation to a neural target using a plurality of electrodes may comprise a programming control circuit configured to determine target energy allocations for the plurality of electrodes based on at least one target pole to provide a target sub-perception modulation field, and normalize the target sub-perception modulation field, including determine a time domain scaling factor to account for at least one property of a neural target or of a neuromodulation waveform, and apply the time domain scaling factor to the target energy allocations.

CLAIM OF PRIORITY

This application claims the benefit of priority under 35 U.S.C. § 119(e)of U.S. Provisional Patent Application Ser. No. 62/451,999, filed onJan. 30, 2017, which is herein incorporated by reference in itsentirety.

CROSS REFERENCE TO RELATED APPLICATION

This application is related to commonly assigned U.S. Provisional PatentApplication Ser. No. 62/451,994, entitled “SUB-PERCEPTION CALIBRATIONUSING SPACE DOMAIN SCALING”, filed on Jan. 30, 2017, which isincorporated by reference in its entirety.

TECHNICAL FIELD

This document relates generally to medical devices, and moreparticularly, but not by way of limitation, to systems, devices, andmethods to provide a neuromodulation field.

BACKGROUND

Neural modulation has been proposed as a therapy for a number ofconditions. Often, neural modulation and neural stimulation may be usedinterchangeably to describe excitatory stimulation that causes actionpotentials as well as inhibitory and other effects. Examples ofneuromodulation include Spinal Cord Stimulation (SCS), Deep BrainStimulation (DBS), Peripheral Nerve Stimulation (PNS), and FunctionalElectrical Stimulation (FES). SCS, by way of example and not limitation,has been used to treat chronic pain syndromes. Some neural targets maybe complex structures with different types of nerve fibers. An exampleof such a complex structure is the neuronal elements in and around thespinal cord targeted by SCS.

Neuromodulation energy may be delivered to provide sub-perceptionmodulation that is therapeutically effective, but the delivery of thesub-perception modulation energy is not perceivable by the patient.Since the patient does not perceive the delivery of sub-perceptionenergy, it can be difficult to accurately program a targetsub-perception field as patient feedback is not available for real-timeadjustments to the modulation.

SUMMARY

This document discusses, among other things, systems and methods todefine electrode parameters for neuromodulation such as sub-perceptionSCS. The present inventors have recognized, among other things, thatreal clinical outcomes depend on patient-to-patient differences inelectrode-tissue coupling and neural excitability and that theallocation of energy to the electrodes for the target pole can beimproved using space domain scaling to compensate for patient-specificdisplacement between electrodes or between electrode and tissue, and/orusing time domain scaling to account for at least one property of aneural target or of a neuromodulation waveform.

An example (e.g. “Example 1”) of a non-transient machine readable mediummay contain program instructions for causing a machine to: determinetarget electrode fractionalization contributions energy allocations fora plurality of electrodes based on at least one target pole to provide atarget sub-perception modulation field; and normalize the targetsub-perception modulation field, including determining a time domainscaling factor to account for at least one property of a neural targetor of a neuromodulation waveform, and applying the time domain scalingfactor to the target energy allocations.

In Example 2, the subject matter of Example 1 may optionally beconfigured such that the determine the time domain scaling factorincludes determine the time domain scaling factor based on a type ofneural structure.

In Example 3, the subject matter of any one or any combination ofExamples 1-2 may optionally be configured such that the determine thetime domain scaling factor includes determine the time domain scalingfactor based on at least one neural structure property, the at least oneneural structure property including a geometrical property or anelectrical property.

In Example 4, the subject matter of any one or any combination ofExamples 1-3 may optionally be configured such that the determine thetime domain scaling factor includes determine the time domain scalingfactor based on a pulse width of the neuromodulation waveform.

In Example 5, the subject matter of any one or any combination ofExamples 1-4 may optionally be configured such that the determine thetime domain scaling factor includes determine the time domain scalingfactor based on a frequency of the neuromodulation waveform.

In Example 6, the subject matter of any one or any combination ofExamples 1-5 may optionally be configured such that the determine thetime domain scaling factor includes determine the time domain scalingfactor based on a duty cycle of the neuromodulation waveform.

In Example 7, the subject matter of any one or any combination ofExamples 1-6 may optionally be configured such that the determine thetime domain scaling factor includes determine the time domain scalingfactor based on a shape or pattern of the neuromodulation waveform.

In Example 8, the subject matter of any one or any combination ofExamples 1-7 may optionally be configured such that the determine thetime domain scaling factor includes determine the time domain scalingfactor based on a type of the neuromodulation waveform.

In Example 9, the subject matter of any one or any combination ofExamples 1-8 may optionally be configured such that the normalize thetarget sub-perception modulation field includes determine the timedomain scaling factor to account for at least one property of the neuraltarget and for at least one property of the neuromodulation waveform.

In Example 10, the subject matter of any one or any combination ofExamples 1-9 may optionally be configured such that the normalize thetarget sub-perception modulation field includes determine the timedomain scaling factor to account for at a first property and a secondproperty selected from the group consisting of: a type of neuralstructure; at least one neural structure property, the at least oneneural structure property including a geometrical property or anelectrical property; and a neuromodulation waveform property. Thewaveform property may include a pulse width of the neuromodulationwaveform; a frequency of the neuromodulation waveform; a duty cycle ofthe neuromodulation waveform; a shape or pattern of the neuromodulationwaveform; and a type of the neuromodulation waveform.

In Example 11, the subject matter of Example 10 may optionally beconfigured such that the determine the time domain scaling factor toaccount for at the first property and the second property includesdetermine a first time domain scaling factor to account for the firstproperty, determine a second time domain scaling factor to account forthe second property, and multiplying the first time domain scalingfactor and the second time domain scaling factor.

In Example 12, the subject matter of any one or any combination ofExamples 1-11 may optionally further comprise program instructions forcausing the machine to calibrate a plurality of electrode groups in theplurality of electrodes where each of the plurality of electrode groupshave an electrode configuration and include an electrode set of at leastone electrode from the plurality of electrodes, wherein the calibratingthe electrode groups includes, for each of the plurality of electrodegroups, delivering modulation energy to a neural target and receivingfeedback, and determining a space scaling factor using the feedback toaccount for actual relative positions between the electrode groups andthe neural target, and further applying the space domain scaling factorto the target energy allocations.

In Example 13, the subject matter of any one or any combination ofExamples 1-12 may optionally be configured such that the determining thetime domain scaling factor includes retrieve the time domain scalingfactor from a lookup table or calculate the time domain scaling factorfrom a modeled analytic relationship.

An example (e.g. “Example 14”) of a method may comprise determiningtarget energy allocations for a plurality of electrodes based on atleast one target pole to provide a target sub-perception modulationfield, and normalizing the target sub-perception modulation field,including determining a time domain scaling factor to account for atleast one property of a neural target or of a neuromodulation waveform,and applying the time domain scaling factor to the target energyallocations.

In Example 15, the subject matter of Example 14 may optionally beconfigured such that the determining the time domain scaling factorincludes determining the time domain scaling factor based on a type ofneural structure.

In Example 16, the subject matter of any one or any combination ofExamples 14-15 may optionally be configured such that the determiningthe time domain scaling factor includes determining the time domainscaling factor based on at least one neural structure property, the atleast one neural structure property including a geometrical property oran electrical property.

In Example 17, the subject matter of any one or any combination ofExamples 14-16 may optionally be configured such that the determiningthe time domain scaling factor includes determining the time domainscaling factor based on a pulse width of the neuromodulation waveform.

In Example 18, the subject matter of any one or any combination ofExamples 14-17 may optionally be configured such that the determiningthe time domain scaling factor includes determining the time domainscaling factor based on a frequency of the neuromodulation waveform.

In Example 19, the subject matter of any one or any combination ofExamples 14-18 may optionally be configured such that the determiningthe time domain scaling factor includes determining the time domainscaling factor based on a duty cycle of the neuromodulation waveform.

In Example 20, the subject matter of any one or any combination ofExamples 14-19 may optionally be configured such that the determiningthe time domain scaling factor includes determining the time domainscaling factor based on a shape or pattern of the neuromodulationwaveform.

In Example 21, the subject matter of any one or any combination ofExamples 14-20 may optionally be configured such that the determiningthe time domain scaling factor includes determining the time domainscaling factor based on a type of the neuromodulation waveform.

In Example 22, the subject matter of any one or any combination ofExamples 14-21 may optionally be configured such that the normalizingthe target sub-perception modulation field includes determining the timedomain scaling factor to account for at least one property of the neuraltarget and for at least one property of the neuromodulation waveform.

In Example 23, the subject matter of any one or any combination ofExamples 14-22 may optionally be configured such that the normalizingthe target sub-perception modulation field includes determining the timedomain scaling factor to account for at a first property and a secondproperty selected from the group consisting of: a type of neuralstructure; at least one neural structure property, the at least oneneural structure property including a geometrical property or anelectrical property; and a neuromodulation waveform property. Theneuromodulation waveform property may include a pulse width of theneuromodulation waveform; a frequency of the neuromodulation waveform; aduty cycle of the neuromodulation waveform; a shape or pattern of theneuromodulation waveform; and a type of the neuromodulation waveform.

In Example 24, the subject matter of Example 23 may optionally beconfigured such that the determining the time domain scaling factor toaccount for at the first property and the second property includesdetermining a first time domain scaling factor to account for the firstproperty, determining a second time domain scaling factor to account forthe second property, and multiplying the first time domain scalingfactor and the second time domain scaling factor.

In Example 25, the subject matter of any one or any combination ofExamples 14-24 may optionally be configured such that the method mayfurther comprise calibrating a plurality of electrode groups in theplurality of electrodes where each of the plurality of electrode groupshave an electrode configuration and include an electrode set of at leastone electrode from the plurality of electrodes, wherein the calibratingthe electrode groups includes, for each of the plurality of electrodegroups, delivering modulation energy to a neural target and receivingfeedback, and determining a space scaling factor using the feedback toaccount for actual relative positions between the electrode groups andthe neural target, and further applying the space domain scaling factorto the target energy allocations.

In Example 26, the subject matter of any one or any combination ofExamples 14-25 may optionally be configured such that the determiningthe time domain scaling factor includes retrieving the time domainscaling factor from a lookup table.

In Example 27, the subject matter of any one or any combination ofExamples 14-26 may optionally be configured such that the determiningthe time domain scaling factor includes calculating the time domainscaling factor from a modeled analytic relationship between a thresholdof the neural target and the at least one property of the neural targetor of the neuromodulation waveform.

An example (e.g. “Example 28”) of a system to program a neuromodulatorto deliver neuromodulation to a neural target using a plurality ofelectrodes may comprise a programming control circuit configured todetermine target energy allocations for the plurality of electrodesbased on at least one target pole to provide a target sub-perceptionmodulation field, and normalize the target sub-perception modulationfield, including determine a time domain scaling factor to account forat least one property of a neural target or of a neuromodulationwaveform, and apply the time domain scaling factor to the target energyallocations.

In Example 29, the subject matter of Example 28 may optionally beconfigured such that system may further comprise an external device thatincludes the programming control circuit and a user interface, whereinthe external device is configured to program parameter sets into animplantable modulation device.

In Example 30, the subject matter of any one or any combination ofExamples 14-26 may optionally be configured such that the programmingcontrol circuit is configured to determine the time domain scalingfactor to account for at least one property of the neural target and toaccount for at least one property of the neuromodulation waveform.

This summary is intended to provide an overview of subject matter of thepresent patent application. It is not intended to provide an exclusiveor exhaustive explanation of the disclosure. The detailed description isincluded to provide further information about the present patentapplication. Other aspects of the disclosure will be apparent to personsskilled in the art upon reading and understanding the following detaileddescription and viewing the drawings that form a part thereof, each ofwhich are not to be taken in a limiting sense.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings, which are not necessarily drawn to scale, like numeralsmay describe similar components in different views. Like numerals havingdifferent letter suffixes may represent different instances of similarcomponents. The drawings illustrate generally, by way of example, butnot by way of limitation, various embodiments discussed in the presentdocument.

FIG. 1 illustrates, by way of example, a portion of a spinal cord.

FIG. 2 illustrates, by way of example, an embodiment of aneuromodulation system.

FIG. 3 illustrates, by way of example, an embodiment of a modulationdevice, such as may be implemented in the neuromodulation system of FIG.2.

FIG. 4 illustrates, by way of example, an embodiment of a programmingsystem such as a programming device, which may be implemented as theprogramming device in the neuromodulation system of FIG. 2.

FIG. 5 illustrates, by way of example, an implantable neuromodulationsystem and portions of an environment in which system may be used.

FIG. 6 illustrates, by way of example, an embodiment of a SCS system,which also may be referred to as a Spinal Cord Modulation (SCM) system.

FIG. 7 illustrates, by way of example, some features of theneuromodulation leads and a waveform generator.

FIG. 8 is a schematic view of a single electrical modulation leadimplanted over approximately the longitudinal midline of the patient'sspinal cord.

FIG. 9 illustrates an embodiment where an electrical modulation lead hasbeen implanted more laterally with respect to the spinal cord, therebyplacing it proximate the dorsal horn of the spinal cord, and the otherelectrical modulation lead has been implanted more medially with respectto the spinal cord, thereby placing it proximate the dorsal column ofthe spinal cord.

FIG. 10 is a schematic view of the electrical modulation lead showing anexample of the fractionalization of the anodic current delivered to theelectrodes on the electrical modulation lead.

FIG. 11 illustrates, by way of example, a schematic illustration of agradient in the longitudinal direction along the axis of the electricalmodulation lead.

FIG. 12 illustrates, by way of example, a schematic illustration of agradient in the transverse direction.

FIG. 13 illustrates, by way of example, equipotential voltage lines fora lead, along with a representation of the lead and the dorsal horns.

FIGS. 14-15 illustrate, by way of example, a substantial uniformelectric field, along with a representation of the lead and the dorsalhorns.

FIG. 16A illustrates, by way of example, mapping of target electricalfields to electrodes; and FIG. 16B illustrates, by way of example, anembodiment for determining fractionalization to achieve an objectivefunction.

FIG. 17 illustrates, by way of example, an embodiment for determiningfractionalization to achieve an objective function with more detail.

FIGS. 18A-18B illustrate, by way of example, mapping a target electricalfield to an electrode array.

FIGS. 19A-19C, illustrate, by way of example, selection of a pluralityof constituent current sources at the locations of the electrodes.

FIG. 20 illustrates an m×n transfer matrix used to determine therelative strengths of constituent current sources.

FIG. 21 illustrates, by way of example and not limitation, a diagram forscaling allocated energy for one or more ideal target poles using a timedomain scaling factor and/or a space domain scaling factor.

FIGS. 22 and 23A-23C illustrate, by way of example and not limitation, aprocess for programming a sub-perception target modulation field andnormalizing the target modulation field to account forpatient-to-patient differences in electrode-tissue coupling and/orneural excitability.

FIG. 24 illustrates a flat spinal cord with uniformly spaced observationpoints and with electrodes uniformly spaced from the spinal cord.

FIG. 25 illustrates a non-uniformly straight spinal cord with electrodesnon-uniformly spaced from the spinal cord.

FIG. 26A illustrates a calculated target field in the ideal environment;

FIG. 26B illustrates a real spinal cord environment; and

FIG. 26C illustrates the moved observation points of the real spinalcord environment.

FIGS. 27A-27B generally illustrate, by way of example and notlimitation, examples of space domain scaling.

FIGS. 28A-28C generally illustrate, by way of example and notlimitation, examples of space domain scaling to compensate forelectrode-to-electrode displacement.

FIG. 29 illustrates some examples of contributing time domain scalingfactors that may be stacked or multiplied together to provide an overalltime domain scaling factor that may be used to normalize a targetsub-perception field.

FIGS. 30A-30C provide an example of time domain scaling factors.

FIG. 31 illustrates a non-limiting example for using time domaintargeting.

FIGS. 32A-32D illustrate, by way of example and not limitation, scalingallocated energy using both space domain and time domain factors.

FIG. 33 illustrates an example of a system with components that may beconfigured to perform various functions discussed herein.

DETAILED DESCRIPTION

Target poles have been used to define electrode parameters for spinalcord stimulation (SCS) such as sub-perception SCS. The present inventorshave recognized, among other things, that the allocation of energy tothe electrodes for the target pole can be improved using space domainscaling to compensate for patient-specific displacement betweenelectrodes or between electrode and tissue, and/or using time domainscaling to account for at least one property of a neural target or of aneuromodulation waveform.

Various embodiments described herein involve spinal cord modulation. Abrief description of the physiology of the spinal cord is providedherein to assist the reader. FIG. 1 illustrates, by way of example, aportion of a spinal cord 100 including white matter 101 and gray matter102 of the spinal cord. The gray matter 102 includes cell bodies,synapse, dendrites, and axon terminals. White matter 101 includesmyelinated axons that connect gray matter areas. A typical transversesection of the spinal cord includes a central “butterfly” shaped centralarea of gray matter 102 substantially surrounded by an ellipse-shapedouter area of white matter 101. The white matter of the dorsal column(DC) 103 includes mostly large myelinated axons that form afferentfibers that run in an axial direction. The dorsal portions of the“butterfly” shaped central area of gray matter are referred to as dorsalhorns (DH) 104. In contrast to the DC fibers that run in an axialdirection, DH fibers can be oriented in many directions, includingperpendicular to the longitudinal axis of the spinal cord. Examples ofspinal nerves 105 are also illustrated, including a dorsal root (DR)105, dorsal root ganglion 107 and ventral root 108. The dorsal root 105mostly carries sensory signals into the spinal cord, and the ventralroot functions as an efferent motor root. The dorsal and ventral rootsjoin to form mixed spinal nerves 105.

SCS has been used to alleviate pain. A therapeutic goal for conventionalSCS programming has been to maximize stimulation (i.e., recruitment) ofthe DC fibers that run in the white matter along the longitudinal axisof the spinal cord and minimal stimulation of other fibers that runperpendicular to the longitudinal axis of the spinal cord (dorsal rootfibers, predominantly), as illustrated in FIG. 1. The white matter ofthe DC includes mostly large myelinated axons that form afferent fibers.While the full mechanisms of pain relief are not well understood, it isbelieved that the perception of pain signals is inhibited via the gatecontrol theory of pain, which suggests that enhanced activity ofinnocuous touch or pressure afferents via electrical stimulation createsinterneuronal activity within the DH of the spinal cord that releasesinhibitory neurotransmitters (Gamma-Aminobutyric Acid (GABA), glycine),which in turn, reduces the hypersensitivity of wide dynamic range (WDR)sensory neurons to noxious afferent input of pain signals traveling fromthe dorsal root (DR) neural fibers that innervate the pain region of thepatient, as well as treating general WDR ectopy. Consequently, the largesensory afferents of the DC nerve fibers have been conventionallytargeted for stimulation at an amplitude that provides pain relief.Current implantable neuromodulation systems typically include electrodesimplanted adjacent, i.e., resting near, or upon the dura, to the dorsalcolumn of the spinal cord of the patient and along a longitudinal axisof the spinal cord of the patient.

Activation of large sensory DC nerve fibers also typically creates theparesthesia sensation that often accompanies conventional SCS therapy.Although alternative or artifactual sensations, such as paresthesia, areusually tolerated relative to the sensation of pain, patients sometimesreport these sensations to be uncomfortable, and therefore, they can beconsidered an adverse side-effect to neuromodulation therapy in somecases. Some embodiments deliver sub-perception therapy that istherapeutically effective to treat pain, for example, but the patientdoes not sense the delivery of the modulation field (e.g. paresthesia).Sub-perception therapy may include higher frequency modulation (e.g.about 1000 Hz or above) of the spinal cord that effectively blocks thetransmission of pain signals in the afferent fibers in the DC. Someembodiments may implement this higher frequency modulation may include1200 Hz or above, and some embodiments may implement this higherfrequency modulation may include 1500 Hz or above. Some embodimentsherein selectively modulate DH tissue, such as the presynaptic terminalsof pain inhibitory neurons in the spinal cord, over DC tissue. Someembodiments selectively stimulate DR tissue and/or dorsal root ganglionover DC tissue to provide sub-perception therapy. As will be describedin further detail below, some embodiments described herein target axonsfrom inhibitory interneurons that propagate in anterior-posteriordirection aligned with an electric field. Certain myelinated presynapticterminals of inhibitory neurons oriented in the anterior-posterior (AP)direction, i.e. in parallel with electric field, may polarize more thantheir unmyelinated, differently oriented counterparts. Polarization mayproduce both subthreshold and suprathreshold effects that result inpositive clinical effects, and sub-threshold progressive effects mayalso explain clinical observations of wash-in and wash-out effects. Theterminal appears to may be the point of the greatest polarization. Theunmyelinated dendrites to not polarize as much.

Such selective modulation is not delivered at these higher frequencies.For example, the selective modulation may be delivered at frequenciesless than 1,200 Hz. The selective modulation may be delivered atfrequencies less than 1,000 Hz in some embodiments. In some embodiments,the selective modulation may be delivered at frequencies less than 500Hz. In some embodiments, the selective modulation may be delivered atfrequencies less than 350 Hz. In some embodiments, the selectivemodulation may be delivered at frequencies less than 130 Hz. Theselective modulation may be delivered at low frequencies (e.g. as low as2 Hz). The selective modulation may be delivered even without pulses(e.g. 0 Hz) to modulate some neural tissue. By way of example and notlimitation, the selective modulation may be delivered within a frequencyrange selected from the following frequency ranges: 2 Hz to 1,200 Hz; 2Hz to 1,000 Hz, 2 Hz to 500 Hz; 2 Hz to 350 Hz; or 2 Hz to 130 Hz.Systems may be developed to raise the lower end of any these ranges from2 Hz to other frequencies such as, by way of example and not limitation,10 Hz, 20 Hz, 50 Hz or 100 Hz. By way of example and not limitation, itis further noted that the selective modulation may be delivered with aduty cycle, in which stimulation (e.g. a train of pulses) is deliveredduring a Stimulation ON portion of the duty cycle, and is not deliveredduring a Stimulation OFF portion of the duty cycle. By way of exampleand not limitation, the duty cycle may be about 10%±5%, 20%±5%, 30%±5%,40%±5%, 50%±5% or 60%±5%. For example, a burst of pulses for 10 msduring a Stimulation ON portion followed by 15 ms without pulsescorresponds to a 40% duty cycle. The selected modulation may bedelivered with fixed widths. Although the target field can be applied toany pulse width that the device is capable of delivering, longer pulseswidths are believed to be more effective.

FIG. 2 illustrates, by way of example, an embodiment of aneuromodulation system. The illustrated system 210 includes electrodes211, a modulation device 212, and a programming system such as aprogramming device 213. The programming system may include multipledevices. The electrodes 211 are configured to be placed on or near oneor more neural targets in a patient. The modulation device 212 isconfigured to be electrically connected to electrodes 211 and deliverneuromodulation energy, such as in the form of electrical pulses, to theone or more neural targets though electrodes 211. The delivery of theneuromodulation is controlled by using a plurality of modulationparameters. The modulation parameters may specify the electricalwaveform (e.g. pulses or pulse patterns or other waveform shapes) and aselection of electrodes through which the electrical waveform isdelivered. In various embodiments, at least some parameters of theplurality of modulation parameters are programmable by a user, such as aphysician or other caregiver. The programming device 213 provides theuser with accessibility to the user-programmable parameters. In variousembodiments, the programming device 213 is configured to becommunicatively coupled to modulation device via a wired or wirelesslink. In various embodiments, the programming device 213 includes agraphical user interface (GUI) 214 that allows the user to set and/oradjust values of the user-programmable modulation parameters.

FIG. 3 illustrates an embodiment of a modulation device 312, such as maybe implemented in the neuromodulation system 210 of FIG. 2. Theillustrated embodiment of the modulation device 312 includes amodulation output circuit 315 and a modulation control circuit 316.Those of ordinary skill in the art will understand that theneuromodulation system 210 may include additional components such assensing circuitry for patient monitoring and/or feedback control of thetherapy, telemetry circuitry and power. The modulation output circuit315 produces and delivers the neuromodulation. Neuromodulation pulsesare provided herein as an example. However, the present subject matteris not limited to pulses, but may include other electrical waveforms(e.g. waveforms with different waveform shapes, and waveforms withvarious pulse patterns). The modulation control circuit 316 controls thedelivery of the neuromodulation pulses using the plurality of modulationparameters. The lead system 317 includes one or more leads eachconfigured to be electrically connected to modulation device 312 and aplurality of electrodes 311-1 to 311-N, where N>2, distributed in anelectrode arrangement using the one or more leads. Each lead may have anelectrode array consisting of two or more electrodes, which also may bereferred to as contacts. Multiple leads may provide multiple electrodearrays to provide the electrode arrangement. Each electrode is a singleelectrically conductive contact providing for an electrical interfacebetween modulation output circuit 315 and tissue of the patient. Theneuromodulation pulses are each delivered from the modulation outputcircuit 315 through a set of electrodes selected from the electrodes311-1 to 311-N. The number of leads and the number of electrodes on eachlead may depend on, for example, the distribution of target(s) of theneuromodulation and the need for controlling the distribution ofelectric field at each target. In one embodiment, by way of example andnot limitation, the lead system includes two leads each having eightelectrodes. Some embodiments may use a lead system that includes apaddle lead.

The neuromodulation system may be configured to modulate spinal targettissue or other neural tissue. The configuration of electrodes used todeliver electrical pulses to the targeted tissue constitutes anelectrode configuration, with the electrodes capable of beingselectively programmed to act as anodes (positive), cathodes (negative),or left off (zero). In other words, an electrode configurationrepresents the polarity being positive, negative, or zero. An electricalwaveform may be controlled or varied for delivery using electrodeconfiguration(s). The electrical waveforms may be analog or digitalsignals. In some embodiments, the electrical waveform includes pulses.The pulses may be delivered in a regular, repeating pattern, or may bedelivered using complex patterns of pulses that appear to be irregular.Other parameters that may be controlled or varied include the amplitude,pulse width, and rate (or frequency) of the electrical pulses. Eachelectrode configuration, along with the electrical pulse parameters, canbe referred to as a “modulation parameter set.” Each set of modulationparameters, including allocated energy to the electrodes which may beprovided as a fractionalized current distribution to the electrodes (aspercentage cathodic current, percentage anodic current, or off), may bestored and combined into a modulation program that can then be used tomodulate multiple regions within the patient.

The number of electrodes available combined with the ability to generatea variety of complex electrical waveforms (e.g. pulses), presents a hugeselection of modulation parameter sets to the clinician or patient. Forexample, if the neuromodulation system to be programmed has sixteenelectrodes, millions of modulation parameter sets may be available forprogramming into the neuromodulation system. Furthermore, for exampleSCS systems may have thirty-two electrodes which exponentially increasesthe number of modulation parameters sets available for programming. Tofacilitate such selection, the clinician generally programs themodulation parameters sets through a computerized programming system toallow the optimum modulation parameters to be determined based onpatient feedback or other means and to subsequently program the desiredmodulation parameter sets.

FIG. 4 illustrates an embodiment of a programming system such as aprogramming device 413, which may be implemented as the programmingdevice 213 in the neuromodulation system of FIG. 2. The programmingdevice 413 may include a storage circuit 418, a programming controlcircuit 419, and a GUI 414. The programming control circuit 419 maygenerate the plurality of modulation parameters that controls thedelivery of the neuromodulation pulses according to the pattern of theneuromodulation pulses. In various embodiments, the GUI 414 includes anytype of presentation device, such as interactive or non-interactivescreens, and any type of user input devices that allow the user toprogram the modulation parameters, such as touchscreen, keyboard,keypad, touchpad, trackball, joystick, and mouse. The storage circuity418 may store, among other things, modulation parameters to beprogrammed into the modulation device. The programming device 413 maytransmit the plurality of modulation parameters to the modulationdevice. In some embodiments, the programming device 413 may transmitpower to the modulation device. The programming control circuit 419 maygenerate the plurality of modulation parameters. In various embodiments,the programming control circuit 419 may check values of the plurality ofmodulation parameters against safety rules to limit these values withinconstraints of the safety rules.

In various embodiments, circuits of neuromodulation, including itsvarious embodiments discussed in this document, may be implemented usinga combination of hardware, software and firmware. For example, thecircuit may be implemented using an application-specific circuitconstructed to perform one or more particular functions or ageneral-purpose circuit programmed to perform such function(s). Such ageneral-purpose circuit includes, but is not limited to, amicroprocessor or a portion thereof, a microcontroller or portionsthereof, and a programmable logic circuit or a portion thereof.

FIG. 5 illustrates, by way of example, an implantable neuromodulationsystem and portions of an environment in which system may be used. Thesystem is illustrated for implantation near the spinal cord. However,the neuromodulation system may be configured to modulate other neuraltargets. The system 520 may include an implantable system 521, anexternal system 522, and a telemetry link 523 providing for wirelesscommunication between implantable system 521 and external system 522.The implantable system is illustrated as being implanted in thepatient's body. The implantable system 521 includes an implantablemodulation device (also referred to as a waveform generator or animplantable pulse generator, or IPG) 512, a lead system 517, andelectrodes 511. The lead system 517 includes one or more leads eachconfigured to be electrically connected to the modulation device 512 anda plurality of electrodes 511 distributed in the one or more leads. Invarious embodiments, the external system 522 includes one or moreexternal (non-implantable) devices each allowing a user (e.g. aclinician or other caregiver and/or the patient) to communicate with theimplantable system 521. In some embodiments, the external system 522includes a programming device intended for a clinician or othercaregiver to initialize and adjust settings for the implantable system521 and a remote control device intended for use by the patient. Forexample, the remote control device may allow the patient to turn atherapy on and off and/or adjust certain patient-programmable parametersof the plurality of modulation parameters.

The neuromodulation lead(s) of the lead system 517 may be placedadjacent, i.e., resting near, or upon the dura, adjacent to the spinalcord area to be stimulated. For example, the neuromodulation lead(s) maybe implanted along a longitudinal axis of the spinal cord of thepatient. Due to the lack of space near the location where theneuromodulation lead(s) exit the spinal column, the implantablemodulation device 512 may be implanted in a surgically-made pocketeither in the abdomen or above the buttocks, or may be implanted inother locations of the patient's body. The lead extension(s) may be usedto facilitate the implantation of the implantable modulation device 512away from the exit point of the neuromodulation lead(s).

FIG. 6 illustrates, by way of example, an embodiment of a SCS system,which also may be referred to as a Spinal Cord Modulation (SCM) system.The SCS system 624 may generally include a plurality (illustrated astwo) of implantable neuromodulation leads 625, an electrical waveformgenerator 626, an external remote controller RC 627, a clinician'sprogrammer (CP) 628, and an external trial modulator (ETM) 629. IPGs areused herein as an example of the electrical waveform generator. Thewaveform generator may be configurable to deliver repeating patterns ofpulses, irregular patterns of pulses where pulses have differingamplitudes, pulse widths, pulse intervals, and bursts with differingnumber of pulses. The waveform generator may be configurable to deliverelectrical waveforms other than pulses. The waveform generator 626 maybe physically connected via one or more percutaneous lead extensions 630to the neuromodulation leads 625, which carry a plurality of electrodes631. As illustrated, the neuromodulation leads 625 may be percutaneousleads with the electrodes arranged in-line along the neuromodulationleads. Any suitable number of neuromodulation leads can be provided,including only one, as long as the number of electrodes is greater thantwo (including the waveform generator case function as a case electrode)to allow for lateral steering of the current. Alternatively, a surgicalpaddle lead can be used in place of one or more of the percutaneousleads. In some embodiments, the waveform generator 626 may include pulsegeneration circuitry that delivers electrical modulation energy in theform of a pulsed electrical waveform (i.e., a temporal series ofelectrical pulses) to the electrodes in accordance with a set ofmodulation parameters.

The ETM 629 may also be physically connected via the percutaneous leadextensions 632 and external cable 633 to the neuromodulation leads 625.The ETM 629 may have similar waveform generation circuitry as thewaveform generator 626 to deliver electrical modulation energy to theelectrodes accordance with a set of modulation parameters. The ETM 629is a non-implantable device that is used on a trial basis after theneuromodulation leads 625 have been implanted and prior to implantationof the waveform generator 626, to test the responsiveness of themodulation that is to be provided. Functions described herein withrespect to the waveform generator 626 can likewise be performed withrespect to the ETM 629.

The RC 627 may be used to telemetrically control the ETM 629 via abi-directional RF communications link 634. The RC 627 may be used totelemetrically control the waveform generator 626 via a bi-directionalRF communications link 635. Such control allows the waveform generator626 to be turned on or off and to be programmed with differentmodulation parameter sets. The waveform generator 626 may also beoperated to modify the programmed modulation parameters to activelycontrol the characteristics of the electrical modulation energy outputby the waveform generator 626. A clinician may use the CP 628 to programmodulation parameters into the waveform generator 626 and ETM 629 in theoperating room and in follow-up sessions.

The CP 628 may indirectly communicate with the waveform generator 626 orETM 629, through the RC 627, via an IR communications link 636 or otherlink. The CP 628 may directly communicate with the waveform generator626 or ETM 629 via an RF communications link or other link (not shown).The clinician detailed modulation parameters provided by the CP 628 mayalso be used to program the RC 627, so that the modulation parameterscan be subsequently modified by operation of the RC 627 in a stand-alonemode (i.e., without the assistance of the CP 628). Various devices mayfunction as the CP 628. Such devices may include portable devices suchas a lap-top personal computer, mini-computer, personal digitalassistant (PDA), tablets, phones, or a remote control (RC) with expandedfunctionality. Thus, the programming methodologies can be performed byexecuting software instructions contained within the CP 628.Alternatively, such programming methodologies can be performed usingfirmware or hardware. In any event, the CP 628 may actively control thecharacteristics of the electrical modulation generated by the waveformgenerator 626 to allow the desired parameters to be determined based onpatient feedback or other feedback and for subsequently programming thewaveform generator 626 with the desired modulation parameters. To allowthe user to perform these functions, the CP 628 may include a user inputdevice (e.g., a mouse and a keyboard), and a programming display screenhoused in a case. In addition to, or in lieu of, the mouse, otherdirectional programming devices may be used, such as a trackball,touchpad, joystick, touch screens or directional keys included as partof the keys associated with the keyboard. An external device (e.g. CP)may be programmed to provide display screen(s) that allow the clinicianto, among other functions, to select or enter patient profileinformation (e.g., name, birth date, patient identification, physician,diagnosis, and address), enter procedure information (e.g.,programming/follow-up, implant trial system, implant waveform generator,implant waveform generator and lead(s), replace waveform generator,replace waveform generator and leads, replace or revise leads, explant,etc.), generate a pain map of the patient, define the configuration andorientation of the leads, initiate and control the electrical modulationenergy output by the neuromodulation leads, and select and program theIPG with modulation parameters in both a surgical setting and a clinicalsetting.

An external charger 637 may be a portable device used totranscutaneously charge the waveform generator via a wireless link suchas an inductive link 638. Once the waveform generator has beenprogrammed, and its power source has been charged by the externalcharger or otherwise replenished, the waveform generator may function asprogrammed without the RC or CP being present.

FIG. 7 illustrates, by way of example, some features of theneuromodulation leads 725 and a waveform generator 726. The waveformgenerator 726 may be an implantable device or may be an external devicesuch as may be used to test the electrodes during an implantationprocedure. In the illustrated example, one of the neuromodulation leadshas eight electrodes (labeled E1-E8), and the other neuromodulation leadhas eight electrodes (labeled E9-E16). The actual number and shape ofleads and electrodes may vary for the intended application. Animplantable waveform generator may include an outer case for housing theelectronic and other components. The outer case may be composed of anelectrically conductive, biocompatible material, such as titanium, thatforms a hermetically-sealed compartment wherein the internal electronicsare protected from the body tissue and fluids. In some cases, the outercase may serve as an electrode (e.g. case electrode). The waveformgenerator may include electronic components, such as acontroller/processor (e.g., a microcontroller), memory, a battery,telemetry circuitry, monitoring circuitry, modulation output circuitry,and other suitable components known to those skilled in the art. Themicrocontroller executes a suitable program stored in memory, fordirecting and controlling the neuromodulation performed by the waveformgenerator. Electrical modulation energy is provided to the electrodes inaccordance with a set of modulation parameters programmed into the pulsegenerator. By way of example but not limitation, the electricalmodulation energy may be in the form of a pulsed electrical waveform.Such modulation parameters may comprise electrode combinations, whichdefine the electrodes that are activated as anodes (positive), cathodes(negative), and turned off (zero), percentage of modulation energyassigned to each electrode (which may also be referred to as allocatedenergy or fractionalized electrode configurations), and electrical pulseparameters, which define the pulse amplitude (measured in milliamps orvolts depending on whether the pulse generator supplies constant currentor constant voltage to the electrode array), pulse width (measured inmicroseconds), pulse rate (measured in pulses per second), and burstrate (measured as the modulation on duration X and modulation offduration Y). Electrodes that are selected to transmit or receiveelectrical energy are referred to herein as “activated,” whileelectrodes that are not selected to transmit or receive electricalenergy are referred to herein as “non-activated.”

Electrical modulation occurs between or among a plurality of activatedelectrodes, one of which may be the case of the waveform generator. Thesystem may be capable of transmitting modulation energy to the tissue ina monopolar or multipolar (e.g., bipolar, tripolar, or more than threepoles) fashion. Monopolar modulation occurs when a selected one of thelead electrodes is activated along with the case of the waveformgenerator, so that modulation energy is transmitted between the selectedelectrode and case. Any of the electrodes E1-E16 and the case electrodemay be assigned to up to k possible groups or timing “channels.” In oneembodiment, k may equal four. The timing channel identifies whichelectrodes are selected to synchronously source or sink current tocreate an electric field in the tissue to be stimulated. Amplitudes andpolarities of electrodes on a channel may vary. In particular, theelectrodes can be selected to be positive (anode, sourcing current),negative (cathode, sinking current), or off (no current) polarity in anyof the k timing channels. The waveform generator may be operated in amode to deliver electrical modulation energy that is therapeuticallyeffective and causes the patient to perceive delivery of the energy(e.g. therapeutically effective to relieve pain with perceivedparesthesia), and may be operated in a sub-perception mode to deliverelectrical modulation energy that is therapeutically effective and doesnot cause the patient to perceive delivery of the energy (e.g.therapeutically effective to relieve pain without perceivedparesthesia).

The waveform generator may be configured to individually control themagnitude of electrical current flowing through each of the electrodes.For example, a current generator may be configured to selectivelygenerate individual current-regulated amplitudes from independentcurrent sources for each electrode. In some embodiments, the pulsegenerator may have voltage regulated outputs. While individuallyprogrammable electrode amplitudes are desirable to achieve fine control,a single output source switched across electrodes may also be used,although with less fine control in programming. Neuromodulators may bedesigned with mixed current and voltage regulated devices.

The energy may be allocated to electrodes to provide a desiredmodulation field. Some non-limiting examples of modulation fields areprovided below.

FIGS. 8-11 illustrate, by way of example, a difference in electricalfield strength in the longitudinal and transverse directions when thecurrent is fractionalized such that the electrical field in thelongitudinal direction generated by the fractionalized current deliveredto each electrode is approximately equal. The voltage at a patient'sspinal cord (especially at the DC fibers) is approximately equal in thelongitudinal direction, resulting in a voltage gradient of approximatelyzero along the DC. This may require different amounts of allocatedenergy to each electrode (e.g. fractionalized current delivered to eachelectrode). Calibration techniques are used to determine the propercurrent fractionalization. With the current fractionalized to aplurality of electrodes on the electrical modulation lead, the resultingfield can be calculated by superimposing the fields generated by thecurrent delivered to each electrode. Moreover each electrical field hasa longitudinal component and a transverse component.

FIG. 8 is a schematic view of a single electrical modulation lead 839implanted over approximately the longitudinal midline of the patient'sspinal cord 840. It is understood that additional leads or leadpaddle(s) may be used, such as may be used to provide a wider electrodearrangement and/or to provide the electrodes closer to dorsal hornelements, and that these electrode arrays also may implementfractionalized current. FIG. 9 illustrates an embodiment where anelectrical modulation lead 941 has been implanted more laterally withrespect to the spinal cord, thereby placing it proximate the dorsal hornof the spinal cord, and the other electrical modulation lead 942 hasbeen implanted more medially with respect to the spinal cord, therebyplacing it proximate the dorsal column of the spinal cord 940. Placementof the lead more proximate to the DH than the DC may be desirable topreferentially stimulate DH elements over DC neural elements for asub-perception therapy. Any other plurality of leads or a multiplecolumn paddle lead can also be used. Longitudinal component of theelectrical field is directed along the y-axis depicted in FIG. 8, and atransverse component of the electrical field is directed along thex-axis depicted in FIG. 8. Some embodiments may include directionalleads with one or more directional electrodes. A directional electrodemay extend less than 360 degrees about the circumference of a lead body.For example, a row of two or more directional electrodes (e.g.“segmented electrodes”) may be positioned along the circumference of thelead body. Activating select ones of the segmented electrodes may helpextend and shape the field in a preferred direction.

FIG. 10 is a schematic view of the electrical modulation lead 1043showing an example of the fractionalization of the anodic currentdelivered to the electrodes on the electrical modulation lead. In orderto provide a simpler illustration, these figures illustratefractionalization using monopolar modulation where a case electrode ofthe waveform generator is the only cathode, and carries 100% of thecathodic current. The fractionalization of the anodic current shown inFIG. 10 does not deliver an equal amount of current to each electrode1044, because this embodiment takes into account electrode/tissuecoupling differences, which are the differences in how the tissueunderlying each electrode reacts to electrical modulation. Also, theends of the portion of the electrical modulation lead include electrodeshaving lower gradient in the longitudinal direction. The magnitude ofthe electrical field tapers down at the ends of the electricalmodulation lead. Fractionalization of the current to the electrodes iscontrolled such that the tissue underlying each electrode in the middleportion of the electrical modulation lead reacts approximately equallyto the electrical modulation, or tissue activation underlying eachelectrode are eliminated. However, the resulting fractionalization isnot equal. In the embodiment shown in FIG. 10, fractionalization of thecurrent to the middle electrodes varies from 10% to 18%, reflecting thevariation in the tissue underlying those electrodes. Thefractionalization across the electrical modulation lead can vary in anymanner as long as the total of fractionalized currents equals 100%.Various embodiments described herein implement a programmed algorithm todetermine the appropriate fractionalization to achieve a desiredmodulation field property (e.g. constant electric field, or constantelectric field magnitude, or constant voltage). Furthermore, asdiscussed in more detail below the allocation of energy to theelectrodes for the target pole may be further improved using spacedomain scaling to compensate for patient-specific displacement betweenelectrodes or between electrode and tissue, and/or using time domainscaling to account for at least one property of a neural target or of aneuromodulation waveform.

FIG. 11 illustrates, by way of example and not limitation, a schematicillustration of a gradient that may exist in the longitudinal directionalong the axis of the electrical modulation lead. The electrical fieldstrength 1145 in the longitudinal direction is plotted over a schematicrepresentation of the electrodes 1144 on the electrical modulation lead1143. The illustration in FIG. 11 shows that the electrical fieldstrength is substantially constant over the middle portion of theelectrical modulation lead, but may form a wave with very smallamplitude because of the gaps between the electrodes in the lead. Thissubstantially constant electrical field forms a small longitudinalgradient, which minimizes activation of the large myelinated axons inthe dorsal column. The illustration in FIG. 11 also shows the electricalfield in the longitudinal direction tapering at the ends of theelectrical modulation lead.

FIG. 12 illustrates, by way of example, a schematic illustration of agradient that may exist in the transverse direction. The transverseelectrical field strength 1245 in the transverse direction is plottedover a schematic representation of the electrical modulation lead 1243and the spinal cord 1240 of the patient. The illustration in FIG. 12shows that the transverse electrical field strength is greatest adjacentthe electrical modulation lead and falls off lateral of the electricalmodulation lead. Use of additional modulation leads to widen theelectrode array may be used to provide desired fractionalization to alsoprovide a region of a substantially constant electric field for adistance along the transverse direction. Substantially constant electricfields may favor modulation of dorsal horn and/or dorsal root neuronalelements over dorsal column neuronal elements. Various embodiments mayuse a substantially constant electric field to target inhibitoryinterneurons that propagate in anterior-posterior direction.

FIG. 13 illustrates, by way of example, equipotential voltage lines fora lead, along with a representation of the lead and the dorsal horns;and FIGS. 14-15 illustrate, by way of example, a substantial uniformelectric field, along with a representation of the lead and the dorsalhorns. The orientation of the electrical field may be selected to targetthe different directions/orientations of the DH elements. To generateelectrical fields in different medio-lateral directions, the electrodesmay have different current fractionalizations in the radial direction.

The SCS system may be configured to deliver different electrical fieldsto achieve a temporal summation of modulation in the DH elements. Forembodiments that use a pulse generator, the electrical fields can begenerated respectively on a pulse-by-pulse basis. For example, a firstelectrical field can be generated by the electrodes (using a firstcurrent fractionalization) during a first electrical pulse of the pulsedwaveform, a second different electrical field can be generated by theelectrodes (using a second different current fractionalization) during asecond electrical pulse of the pulsed waveform, a third differentelectrical field can be generated by the electrodes (using a thirddifferent current fractionalization) during a third electrical pulse ofthe pulsed waveform, a fourth different electrical field can begenerated by the electrodes (using a fourth different currentfractionalized) during a fourth electrical pulse of the pulsed waveform,and so forth. These electrical fields may be rotated or cycled throughmultiple times under a timing scheme, where each field is implementedusing a timing channel. The electrical fields may be generated at acontinuous pulse rate, or may be bursted on and off. Furthermore, theinterpulse interval (i.e., the time between adjacent pulses), pulseamplitude, and pulse duration during the electrical field cycles may beuniform or may vary within the electrical field cycle.

An embodiment may modify the fractionalized current delivered to eachelectrode to minimize the electrical field gradient in the longitudinaldirection, so as to minimize activation of the DC elements. Minimizingactivation of the DC elements can include a model-based calculation,where the model includes the information from the calibration. Adiscrete activating function can be calculated by the formula:AF(n)=Ga/(π×d×1)×[Ve(n−1)−2 Ve(n)+Ve(n+1)], wherein Ga is the axonalintermodal conductance, d is the axonal diameter, 1 is the length of thenode of Ranvier, Ve(n) is the strength of the electric field at the nodefor which the activating function is determined, Ve(n−1) is the strengthof the electric field at the node preceding the node for which theactivating function is determined, and Ve(n+1) is the strength of theelectric field at the node following the node for which the activatingfunction is determined. Using this formula, the discrete activatingfunction is calculated from the conductance normalized to the surfacearea of the node of Ranvier.

Modulation thresholds vary from patient to patient and from electrode toelectrode within a patient. An electrode/tissue coupling calibration ofthe physical electrodes may be performed to account for these differentmodulation thresholds and provide a more accurate fractionalization ofthe current between electrodes. For example, perception threshold may beused to normalize the physical electrodes. The RC or the CP may beconfigured to prompt the patient to actuate a control element, onceparesthesia is perceived by the patient. In response to this user input,the RC or the CP may be configured to respond to this user input bystoring the modulation signal strength of the electrical pulse traindelivered when the control element is actuated. Other sensed parameteror patient-perceived modulation values (e.g. constant paresthesia, ormaximum tolerable paresthesia) may be used to provide theelectrode/tissue coupling calibration of the physical electrodes. Thesesensed parameter or patient-perceived modulation values may be used toestimate the current fractionalization by minimizing the sum of thesquare of the discrete activating function divided by the determinedvalue (e.g. perception threshold) at each physical electrode on anelectrical modulation lead as is described in more detail below.Squaring the discrete activating function, or any driving force from theelectrical field, eliminates the differences in depolarizing andhyperpolarizing fields. The current fractionalization that results in aminimize sum minimizes the field gradient in the longitudinal direction.

Various embodiments of the present subject matter may use “targetmultipoles.” For example, target multipoles may be used to provide alinear field that may maximize the electric field in a region whileminimizing the activation of dorsal columns. These target multipoles maybe referred to as “ideal” or “virtual” multipoles. Each target pole of atarget multipole may correspond to one physical electrode, but may alsocorrespond to a space that does not correspond to one electrode, and maybe emulated using electrode fractionalization. By way of examples, U.S.Pat. Nos. 8,412,345 and 8,909,350 describe target multipoles. U.S. Pat.Nos. 8,412,345 and 8,909,350 are hereby incorporated by reference intheir entirety. Target multipoles are briefly described herein.

A stimulation target in the form of a target poles (e.g., a targetmultipole such as a target bipole or target tripole or a targetmultipole with more than three target poles) may be defined and thestimulation parameters, including the allocated energy values (e.g.fractionalized current values) on each of the electrodes, may becomputationally determined in a manner that emulates these target poles.Current steering may be implemented by moving the target poles about theleads, such that the appropriate allocated energy values (e.g.fractionalized current values) for the electrodes are computed for eachof the various positions of the target pole.

With reference to FIG. 16A, the CP may be configured to accept relativeelectrode positions as well as a single electrode field model includingcoupling efficiency 1646 and a representation of a target electricalfield 1647 (instead of including these parameters in the design ofnavigation tables) and to map the target electrical field to theelectrodes 1648, thereby yielding energy allocation (e.g. the polaritiesand percentages of electrical current to be associated with theelectrodes 1649), as well as a boost or scaling factor 1650 for globallyadjusting the magnitude of the total energy (e.g. current) supplied tothe electrodes. Electrode locations and information about the desiredelectrical field may be independently inputted into the algorithm.

FIG. 16B illustrates, by way of example, an embodiment for determiningenergy allocation (e.g. current fractionalization) to achieve anobjective function. An objective function refers to a function withdesirable characteristics for modulating the targeted tissue. Theobjective function may also be referred to as an objective targetfunction. An objective function 1651 for a desired field shape may beidentified for a given volume of tissue. By way of example and notlimitation, an objective function may provide a broad and uniformmodulation field such as a constant E (electric field), a constant |E|(electric field magnitude), and a constant voltage. The lead andelectrode configuration 1652 are also identified, as well as calibrationfor the physical electrode-to-tissue coupling 1653. A function 1654 isperformed that is dependent on the objective function, the lead andelectrode configuration and the calibration. The function 1654 may alsobe dependent on other inputs (e.g. a methodology/algorithm, anoptimization method, a constraint, and the like). The result of thefunction is the allocation of modulation energy (e.g. currentfractionalization) 1655 for each electrode to achieve the objectivefunction.

FIG. 17 illustrates, by way of example, an embodiment for determiningenergy allocation (e.g. current fractionalization) to achieve anobjective function with more detail. An objective target function 1751(e.g. constant E) is provided as an input to a process. Other inputs tothe process include a configuration option 1756, a lead configuration1757 and electrode contact status 1758, and a threshold 1759 such as acurrent threshold or more particularly a monopolar current threshold.The lead configuration 1757 and contact status 1758 identify anelectrode arrangement, identifying a position of each electrode todetermine the field. The overall field is a superimposed field from eachelectrode. The configuration option 1756 refers to monopolar (samepolarity for all activated electrodes) and multipolar options (combinedanode and cathodes in field). The threshold is used to compensate forelectrode/tissue coupling differences.

The contacts for stimulation may be determined automatically or manually1760 from the lead configuration and contact status. A selected fieldmodel may be used to estimate the field induced by unit current from thecontact 1761. The field is calibrated using the threshold 1762. Forexample, the unit current field may be weighted. Constituent sources areformed based on the selected contacts 1763, and a transfer matrix 1764is constructed to use to compute the minimal mean square solution 1766using contributions from the constituent sources and using a specifiedtarget field 1765. The solution can be used to compute the currentfractionalization on each contact 1767.

With reference to FIGS. 18A-18B, the CP may map a target electricalfield to the electrode array by estimating the field potential values(or some other linear electrical parameter, such as an activatingfunction, current density, etc.) of the target field at a plurality ofspatial observation points. The CP may accomplish this by determiningthe desired locations of target current source poles relative to theelectrode array, and modeling an electrical field generated by thetarget current source poles to determine desired field potential valuesat the spatial observation points (e.g., using analytical and/ornumerical models).

Although target current source poles are one way to represent a “targetelectrical field”, other representations of target fields may be used.The locations of the target current source poles may be determined in amanner that places the resulting electrical field over an identifiedregion of the patient to be stimulated. The spatial observation pointsmay be spaced in a manner that would, at the least, cover the entiretissue region to be stimulated and/or a tissue region that should not bestimulated. The locations of the target current source poles may bedefined by the user, and may be displayed to the user along with theelectrode locations, which as briefly discussed above, may be determinedbased on electrical measurements taken at the electrodes. Referring toFIGS. 19A-19C, the CP may select, or allow a user to select, a pluralityof constituent current sources at the locations of the electrodes. Thelocations of the electrodes may be determined based on measurementstaken at the electrodes in response to sub-threshold electrical signalstransmitted between the electrodes. In the illustrated target bipole afirst constituent current source can be defined at the locations ofelectrodes E1 and E2 as −100% and +100%, respectively (FIG. 19A); asecond constituent current source can be defined at the locations ofelectrodes E2 and E3 as −100% and +100%, respectively (FIG. 19B); athird constituent current source can be defined at the locations ofelectrodes E3 and E4 as −100% and +100%, respectively (FIG. 19C); and soon. It is noted that these figures are provided to an example ofconstituent sources. Other combinations can be used. It is further notedthat the system may be designed to use voltage or current sources as theelectrical sources in the constituent sources. The location of each ofthe electrodes is included within at least one of the constituentsources. Thus, the minimum number of constituent sources may be equal tothe number of contacts less one, or may equal the number of contacts(e.g., if a monopole is used as the constituent source).

Once the constituent sources are selected, the CP may determine therelative strengths of the constituent current sources that, whencombined, result in estimated electrical field potential values at thespatial observation points that best matches the desired field potentialvalues at the spatial observation points. In particular, the CP maymodel the constituent current sources (e.g., using analytical and/ornumerical models) and estimate the field potential values per unitcurrent (V/mA) generated by each of the constituent current sources atthe spatial observation points, and may generate an m x n transfermatrix (shown in FIG. 20) from the estimated field potential values perunit current, with m equaling the number of spatial observation pointsand n equaling the number of constituent sources. The relative strengthsof the constituent current sources may be determined using anoptimization function that includes the transfer matrix A and thedesired field potential values. The above description uses fieldpotential or voltage values as an example of parameter values that canbe associated with each of the observation points. Other parameters maybe used as well including derived parameters values such a derivative,activating function, total driving function, and the like.

The optimization function may be a least-squares (over-determined)function expressed as: |φ−Aĵ|2, where φ is an m-element vector of thedesired electrical field parameter values (e.g. desired field potentialvalues), A is the transfer matrix, and ĵ is an n-element vector of thestrengths of the constituent current sources. The constituent currentsource strengths ĵ may be solved such that the optimization function|φ−Aĵ|2 is minimized. The square difference is minimized if φ=Aĵ. Oneapproach for solving this problem may be to invert the transfer matrix Aand pre-multiply, such that A−1=φA−1Aĵ, which yields the solutionĵ=A−1φ. Once the strengths of the constituent current sources aredetermined, the CP converts these strengths to energy allocations (e.g.current distributions) on the electrodes in the form of a polarity andpercentage.

The remainder of this document discusses various embodiments that relateto optimizing electrode configurations to be used with sub-perceptionSCS. The sub-perception SCS may include, but is not limited to, burstSCS, high rate SCS, long pulse width, and/or high density forms of SCS.The burst SCS may include 2 to 7 pulses wherein each burst of pulses mayhave a pulse frequency, also referred to as an intraburst pulsefrequency, within a range between 250 Hz to 500 Hz. The burst-to-burstfrequency (also referred to as an interburst frequency, may be within arange of 20 Hz to 60 Hz. High rate SCS may include SCS with a frequencyequal to or greater than 1 kHz. Long pulse width SCS may include pulsewidths of 90 microseconds or more for the active phase, rather than thetotal length of the waveform, of a pulse. High density forms of SCS mayinclude SCS using high duty cycle or high “charge per phase” waveforms.A waveform may be defined as “high density” if charge delivered per unittime is above a threshold. By way of example and not limitation,waveforms may be considered to be “high density” if over 20% of the dutycycle consists of an active stimulation phase. A high densityclassification is based more on a duty cycle and/or a charge per timemeasurement rather than a pulse rate. For example, both a 500 Hz and a 1kHz waveform may be defined as “high density” if the proportion of theduty cycle occupied by the active phase exceeds a threshold (e.g. 20% to25%).Collectible patient feedback data may be used to provide a feedbackmetric used to optimize the energy allocations to electrodes (e.g.electrode fractionalizations) and total amplitudes to best match auser-specified target pole. Examples of such collectible feedback datamay include, but are not limited to patient-provided paresthesia data(e.g. amplitude and sensation) such as may be used to identifyparesthesia threshold, evoked action potentials (ECAPs) such as ECAPsrepresenting activity in the dorsal roots, dorsal horn, and/or dorsalcolumn, and Local Field Potentials (LFPs).

As discussed above, target poles with inverse modeling have been used todefine electrode parameters for SCS. Additionally, U.S. Pat. No.8,412,345, entitled “System and Method for Mapping Arbitrary ElectricFields to Pre-Existing Lead Electrodes” which is incorporated herein byreference in its entirety, discusses the use of target poles, which havealso been referred to as “ideal” poles. Also, as discussed above and inU.S. Pat. Pub. No. 20160082251, entitled “Neuromodulation Specific toObjective Function of Modulation Field for Targeted Tissue” which isincorporated herein by reference in its entirety, target poles can bespecified to provide field features to target neural elements.

However, real clinical outcomes depend on patient-to-patient differencesin electrode-tissue coupling and neural excitability. For sub-perceptionmodulation for which the patient does not perceive paresthesia oranother indication of the delivered energy, patient feedback is notavailable for real-time adjustments to the modulation.

For example, electrode-tissue coupling may be affected by the cerebralspinal fluid (CSF) space, which may vary by patient and by the positionalong the spinal column. The patient-specific and position-specificdifferences in electrode-tissue coupling affect the field geometry.Various embodiments of the present subject matter provide space domainscaling to account for displacement (e.g. a distance in a givendirection) between electrodes or between electrode and tissue. Also,different neural tissue exhibit different excitability to the samefield. For example, synaptic terminals and axons have differentexcitability to modulation fields. Various embodiments of the presentsubject matter provide time domain scaling for targeted neural tissue.Various embodiments of the present subject matter may provide both spacedomain scaling and time domain scaling for targeted neural tissue.

FIG. 21 illustrates a diagram in which a time domain scaling factor 2168and/or a space domain scaling factor 2169 are applied to allocatedenergy (e.g. target electrode fractionalization contributions) 2170 forone or more ideal target poles. The scaling factor(s) may serve as amultiplier to the allocated energy of each electrode. Further, a productof the time domain scaling factor and the space domain scaling factormay be applied to provide an overall scaling factor to allocated energyfor the ideal target pole(s). Also, a time domain weight factor 2171 maybe applied to the time domain scaling factor, and/or a space domainweight factor 2172 may be applied to the space domain scaling factor.The result of the scaling is normalized target pole(s) 2173, whereallocated energy (e.g. electrode fractionalization contributions) arenormalized to address differences in electrode-tissue coupling and/orneural excitability.

Space Domain Scaling

FIG. 22 illustrates a process for programming a sub-perception targetmodulation field and normalizing the target modulation field to accountfor patient-to-patient differences in electrode-tissue coupling and/orneural excitability. At 2274 target pole(s) to provide a targetsub-perception modulation field may be programmed. For example, aphysician or other user may define target pole(s), which can then bemoved along the neural anatomy using electrodes operably positioned theneural anatomy. The defined target poles may be defined to provide adesired neuromodulation field (e.g., a dorsal horn stimulation (“DHS”)field, a linear bipole, etc.). The physician or other user may definethe location for the target pole(s) to provide the target sub-perceptionmodulation field at a location based on pain etiology. This targetsub-perception modulation field may be uniform across electrodes. In anexample illustrated in FIG. 23A, the target poles are defined as threecathodes and three anodes on each lead.

At 2275, electrode groups in the electrode array(s) are calibrated. Theelectrode groups may be one electrode for monopolar stimulation, twoelectrodes for bipolar stimulation, three electrodes for tripolarstimulation, or multiple electrodes for multipolar stimulation. Theability to test specific electrode groups may be more accurate indetermining the subjective and/or object responses to modulation fieldsthat use more than one target poles. Each of the electrode groups to betested, which may include one or more electrodes, may be turned onsequentially and/or cycled individually up to a stimulus setting(amplitude, pulse width, relevant stimulation frequency) that issufficient to produce sensation for subject feedback or a biomarker forobjective feedback. The cycling may be automatic or guided by aphysician or other user. For example, a physician or other user maylimit electrodes over which cycling will happen.

At 2276, subjective or objective feedback may be received to provide apatient-specific metric for the patient's response to the stimulation.Examples of such metrics may include but are not limited to tolerabilityor perception thresholds, and spatial distribution of the perception. Anexample of subjective feedback may include patient reports ofparesthesia. Examples of objective feedback may include, but are notlimited to, sensed evoked compound action potentials (ECAPs) over dorsalhorn, local field potentials (LFPs), and dorsal root potential(indicating primary afferent depolarization) recorded by anotherelectrode, biopotential templates, signal amplitudes, signal-to-noiseratio of electroneurograms (ENGs), and latency between stimulationartifact and evoked action potentials. One or more patient-specificmetrics may be recorded for use in normalizing the target sub-perceptionmodulation field. By way of example and not limitation, some metrics mayinclude the lowest value, the highest value, the mean value or anotheraggregate value representing a quantitative output metric that may beuser-defined or designed into the system. In an example illustrated inFIG. 23B, each electrode in the target poles for the right lead in FIG.23A are tested, and the amplitude at which the sensation or biomarker ispresent is listed alongside of the electrode.

At 2277, the target sub-perception modulation field is normalized forthe patient. The target pole(s) referenced in the calibration iscalculated with the assumption that the patient' spinal cord is uniformand flat. Values for an electrode's contribution to the sub-perceptionmodulation field may be scaled in proportion to the magnitude of theoutput metric that was recorded for that electrode. This adjustment maybe further adjusted according to a user-specified or built-in neuraltarget, the pulse width of stimulation, the frequency of stimulation,the waveform shape, or another stimulation-relevant factor (time domainscaling). In the example illustrated in FIG. 23C, the normalized scalingfactor for each of the electrodes is illustrated alongside of theelectrode in proportion to the magnitude of the amplitude at which thesensation or biomarker was present as illustrated in FIG. 23B.

As discussed above, inverse modeling method matchespotentials/fields/activation functions produced by an electrodeconfiguration to potentials/fields/activating functions specified by anidealized target pole. The observation points are defined. Prior systemsassumed a constant electrode tissue coupling efficiency by assuming aconstant distance between the electrode contacts and the observationpoints. For example, the spinal cord and electrode arrays were uniformand straight. FIG. 24 illustrates a flat spinal cord 2478 with uniformlyspaced observation points 2479 and with electrodes 2480 (illustrated asfour electrodes although there may be more) uniformly spaced from thespinal cord.

However, in reality, the electrode may not be fully aligned, the fieldmay not be fully aligned, and/or the spinal cord is not perfectlystraight. FIG. 25 illustrates a non-uniformly straight spinal cord 2578with electrodes 2578 non-uniformly spaced from the spinal cord. Thedistances between the electrodes 2580 and the tissue vary, asrepresented by the different distances Z1, Z2 and Z3. Unlike priorsystems, the present subject matter may recalculate or redefine theobservation points 2579 based on tissue inhomogeneities.

Various embodiments may adjust the spatial observation points used tocalculate the contributions of active electrodes to a target pole or totarget poles such as target bipoles, target tripoles or other targetmultipoles. The adjustments to the spatial observation points 2579 maybe based on characteristics of the target field and/or environment. Forexample, the adjustments to the spatial observation points 2579 may bebased on the coupling strength between the neural tissue in the spinalcord 2578 and the electrode 2580 or patient-reported differences inparesthesia thresholds across electrode contacts.

FIG. 26A illustrates a calculated target field in the ideal environmentin which the observation points 2679, which may be defined using aCartesian coordinate system (x, y, z), are pre-set or placed/seededaccording to the number of electrodes 2680 implanted and/or seeded forstimulation. In the example illustrated in FIG. 26A, the calculatedtarget field in the ideal environment includes fractionalized electrodeamplitudes for the cathodes of a target multipole that are given aspercentages (75% and 25%), and fractionalized amplitudes for the anodesof the target multipole that are also given as percentages (−25% and−75%). These fractionalized electrode amplitudes appropriately allocateenergy to provide a target cathode 2681 and target anode 2682. FIG. 26Billustrates a real spinal cord environment, which may be estimatedduring the calibration of the electrode groups using a feedback metricderived using objective and/or subjective measures. Each of theelectrode groups may include one or more electrodes per group. Thefeedback metric may provide a scaling factor for the allocated energy ateach electrode to normalize the field to the real spinal cordenvironment. In the example illustrated in FIG. 26B, the scaling factorsfor the electrodes may be 1.5×, 3.0×, 3.0× and 1.0×. A target field(+electrode fractionalizations) of arbitrary location and angle may befirst calculated assuming the ideal environment. The spatial observationpoints may have voltage values φe(x,y,z), or longitudinal electric fieldvalues E(x, y, z). Other derived values may also be used such asderivatives, activating functions, total driving functions and the like.Old values of Φe, E are kept for a given spatial observation point, butthe point coordinates are moved to provide adjusted observation points,as generally illustrated in FIG. 26C, according to the thresholdsdetermined using feedback metric generated from objective measures (e.g.CDP, ECAP, LFP) or subjective measures (e.g. patient-reportedparesthesia) for each individual electrode or target pole that wastested (e.g. 8 mm bipole, tripole, multipole). The difference between anexpected value of a feedback measure (e.g. ECAP amplitude) and theactual recorded feedback measure can be used to adjust the location ofthe observational portions that are used to determine the energyallocation to the electrodes. Thus, spinal geometry variations for areal spinal cord environment can be accommodated by changing the spatialobservation point coordinates. The inverse algorithm may then be usedwith the adjusted observation points. A benefit of moving theobservation points is improved optimization using a least-squares(over-determined) function.

FIGS. 27A-27B generally illustrate, by way of example and notlimitation, examples of space domain scaling. The calibrationcalculation used to normalize the allocated energy may involve simpleproportional rebalancing or a more complex inverse modeling scheme. FIG.27B illustrates a non-uniform spinal cord 2778, and allocated energyvalues 2783 (e.g. current fractionalizations represented using bothpercentages and amplitudes) for electrodes 2780 calculated for idealtarget poles that assumes uniformity in the spinal cord and uniformityin the alignment between the spinal cord and the electrodes. In theillustrated example, the common total amplitude is 1.5 mA, and thefractionalizations for the ideal target poles are 1.125 mA (or 75%) and0.375 mA (or 25%) for the anodic constituent sources, and −0.375 mA (or−25%), and −1.125 mA or (−75%) for the cathodic constituent sources.Similar to the previous example, the objective (e.g. biomarker such asCDP, ECAP, LFP threshold) and/or subjective feedback (e.g.patient-reported paresthesia) to the calibration of the electrode groups(one or more electrodes per group) provide a space domain scaling factor2784 normalizing the field to the real spinal cord environment (e.g.1.5×, 3.0×, 3.0× and 1.0×).

A linear recalibration process or non-linear recalibration process 2785may be used to normalize to the greater sum of anodic or cathodiccurrents. For example, the recalibration process 2785 may be aproportional recalibration process. The baseline for the recalibrationprocess may be a common total amplitude for the ideal currents on theelectrodes (e.g. 1.125 mA+0.375 mA=1.5 mA). The calibration may then bethe product of the ideal current contribution and the feedback metricfor each electrode or electrode group divided by the common totalamplitude (1.5 mA). Therefore, in the illustrated the energycontribution of the first electrode is 1.125×1.5/1.5=1.125, the energycontribution of the second electrode is 0.375×3.0/1.5=0.75, the energycontribution of the third electrode is −0.375×3.0/1.5=−0.75, and theenergy contribution of the fourth electrode is 0.375×3.0/1.5=0.75.

It is noted that the total anodic current will equal the total cathodiccurrent. Extra cathodic current or extra anodic current may be allocatedto the case electrode of the waveform generator. In the illustratedrecalibration example 2785, the anodic currents add up to 1.875 mA(1.125+0.75=1.875) and the cathodic currents add up to 1.5 mA (−0.75mA−0.75 mA=−1.5 mA). As the total anodic currents (1.125 mA+0.75mA=1.875 mA) is larger than the total cathodic currents (0.75 mA+0.75mA=1.5 mA), the allocated energy may be normalized to the 1.875 mA valueof the total anodic currents. The normalization includes the idealtarget energy allocations multiplied by the feedback metric divided bythe normalized value. Thus, the contribution of the electrodes may becalculated as follows: 1.125/1.875=60%; 0.75/1.875=40%;−0.75/1.875=−40%; and −0.75/1.875=−40%. The remaining 20% of the anodiccurrent may go onto the case of the implanted pulse generator.

In an observation point movement process to recalibrate, as generallyillustrated at 2786, values for the potential (De or electric field E atthe spatial observation point are not recalculated. Rather, the distanceof the spatial observation points may be moved based on the space domainscaling factors determined from the subject and/or objective feedback.Thus, rather than scaling raw amplitude, the space domain scalingfactors 2784 may be used to scale the spatial observation pointdistances. The baseline for the observation point movement recalibrationprocess may be a common total amplitude for the ideal currents on theelectrodes (e.g. 1.125 mA+0.375 mA=1.5 mA). Therefore, the distancebetween the observation points and the first electrode does not change(1.5/1.5=1), but the distance of the second and third electrodes isdoubled (3/1.5=2) and the distance of the fourth electrode is ⅔ (1/1.5=⅔). In some embodiments, the calibration can globally changeweighting for the inverse matrix.

Furthermore, in some embodiments, the spatial observation points may berepositioned based on electrode geometry, rather than or in addition tospinal geometry. FIGS. 28A-28C generally illustrate, by way of exampleand not limitation, examples of space domain scaling to compensate forelectrode-to-electrode displacement. By way of example and notlimitation, U.S. Pat. No. 8,380,301, which is incorporated herein byreference in its entirety, discusses determining relative positioningbetween neurostimulation leads. An electric field may be generated usinga first electrode (stimulating electrode) on a lead, and a referenceelectric parameter may be measured at a reference electrode (recordingelectrode) on the same lead or as generally illustrated in FIG. 28A, therecording electrode may be on a second lead where the distance betweenthe stimulation and recording electrodes is known. The electricparameter may be measured using second electrode whose distance from thestimulation electrode is not known (e.g. a recording electrode on asecond lead whose position is not known). A relationship between themeasured electric parameter at the second electrode and at the referenceelectrode, along with the reference distance, may be used to determine adistance between the first and second electrodes. By way of example andnot limitation, the measured electric parameter may be an impedance or afield potential. For example, a change in voltage (a change from thewaveform 2887A representing the voltage recorded in FIG. 28A to thewaveform 2887B representing the voltage recorded in FIG. 28B) may beused to determine the separation between the recording and stimulationelectrodes. Various embodiments of the present subject matter maygenerate a target pole, and calculate values at observation pointsbefore performing the calibration. For example, a point source equationmay written as follows: ΔV=I_0/

4πσr1

−I0

4πσr2

. The variable r2 may be solved, and the observation point y,zcoordinates may be moved by Δr. Bessel functions, finite element models,can be used or pre-computed for use to calibrate based on ΔV so long asequations and methods can relate distance from electrode to a change inthe obtained signals. Imaging registration/image processing oruser-defined electrode separation (e.g. on dragging and dropping leadbodies on a representation of a spinal anatomy) can be used to scale aswell. The spatial observation points may be repositioned with thedetected position of the electrodes, but the voltage or electric fieldor activation function values are not recalculated for the repositionedobservation points.

Time Domain Scaling

Calibrations may also vary according to the neural element(s) beingtargeted, especially if multiple field shapes and target poles meant totarget distinct neural populations are placed. Various embodiments mayscale the allocated energy (e.g. electrodefractionalizations/amplitudes) to provide the sub-perception fieldaccording to the electrode-to-electrode relative thresholds and aspecific, user-defined neural target.

The threshold current required to stimulate excitable tissue has arelationship to a pulse duration, where shorter pulse widths requirelarger current amplitudes to stimulate the excitable tissue, and longerpulse widths require smaller current amplitudes to stimulate theexcitable tissue. This relationship between pulse widths and stimulationthreshold (amplitude) may be plotted as a strength duration curve.However, strength duration concepts are not limited to pulsedstimulation, as these concepts may also be applied to different waveformshapes. Strength-duration relationships may also differ by waveformshape, and separate strength-duration equations may be fit/saved foreach waveform type (e.g. passive recharge vs. biphasic active rechargevs. sinusoidal). Strength-duration curves from different waveforms maybe displayed at the same time and compared, as shown, for userreference. A user may be presented with strength-duration curvecorresponding to neural element being targeted that may adapt after userchanges settings. For example, when a neural element and a waveform areselected at same time, then multipliers from neural element effect andwaveform effect may be stacked by multiplying the neural element factorwith the waveform factor, and applying the resulting product to theoriginal target pole configuration. Strength-duration relationships mayalso differ by waveform shape, and separate strength-duration equationsmay be fit/saved for each waveform type (e.g. passive recharge vs.biphasic active recharge vs. sinusoidal). Visually, strength durationcurves for different neural element targets may differ. Strengthduration curve may be displayed as current/voltage vs. pulse width ornormalized threshold vs. pulse width.

FIG. 29 illustrates some examples of contributing time domain scalingfactors that may be stacked or multiplied together to provide an overalltime domain scaling factor that may be used to normalize a targetsub-perception field in a manner that may account for neural structure,size, pulse widths, frequencies, waveform shapes and/or waveform typesto provide a scaling factor for each electrode group (monopolar,bipolar, tripolar, or other multipolar arrangement). For example,scaling factors (i.e. by how much a given threshold and total electrodefractionalization is scaled by) may vary by various neuron-related andwaveform-related variables, including but not limited to structure type(e.g. cell, axon, terminal) 2988, neural structure property 2989 such asa geometrical property (e.g. size such as a nerve diameter) or anelectrical property, waveform pulse width 2990, rate 2991, duty cycle2992, waveform shape or pattern 2993, and waveform such as a passiverecharge or biphasic active recharge 2994. Some scaling factors will bepre-determined off-line (e.g. waveform effects, fiber diameter effects),and others may vary according to an internal lookup table or may becalculated internally using an analytical equation that relatesthreshold to parameter (e.g. strength-duration curve thresholdmultipliers, rate multipliers). An overall time domain scaling factor,based on one or more of the contributing time domain scaling factors maybe determined via a lookup table or calculated based on a model.

In a non-exclusive embodiment, strength-duration relationships (Weiss,Lapicque, or otherwise) derived from offline simulations and/or on-boardbiophysical simulators may be saved on the device as a lookup table.That is, simulation apriori may be used to derive a scaling factor. Thestored lookup table may be used to scale individual thresholds atdifferent electrodes to maintain target pole effects across differentneural elements. The lookup table may be specific to a specificcombination of a waveform and target. In some embodiments, a built-ingraphical user interface (GUI) function may be designed to enable a userto specify different neural targets at distinct electrodes and electrodegroups.

FIGS. 30A-30C provide an example of time domain scaling factors. In theillustrated example, two leads that uses two timing channels to targettwo areas (e.g. Target 1 and Target 2). FIG. 30A illustrates thedifferent strength duration curves for a pulse waveform and sinusoidalwaveform which generally illustrates a time domain scaling factor forthe different waveforms based on the effectiveness of these waveforms toexcite the neural tissue. The system may receive selections from theuser through the GUI to identify a neural target by nerve size in μm orby type (e.g. terminal, dorsal column (DC) axon, dorsal root (DR) axon,or nerve cell). Each of these selections may be associated with a timedomain scaling factor that also provides an indication of theexcitability of those neural targets.

In some embodiments, an algorithm may automatically specify differenttargets depending on the waveform being delivered. By way of example andnot limitation, a 50 Hz signal may default to dorsal columns, and a highrate stimulation may default to terminals. Various embodiments of thesystem may display scaling factors to the user and/or strength-durationcurves at a given frequency.

For example the pulse width for the first lead (Target 1) is illustrated200 μs and the pulse width for the second lead (Target 2) is illustratedas 90 μs and a frequency of 1.2 kHz. A different multiplication may beapplied for the first lead depending on the nerve size of terminals. Inthe illustrated non-limiting example, a nerve size of 5.7 μm may have afactor of 1, a nerve size of 2.5 may have a factor of 2, and a nervesize of 1.3 μm may have a factor of 4. Similarly, a differentmultiplication may be applied for the second lead depending on theneural target, such as but not limited to terminal, dorsal column (DC)axon, dorsal root (DR) axon, or nerve cell, and waveform. Examples ofwaveform may include, but are not limited to pulse, rectangular,sinusoidal, or custom.

Space domain factors may be used to first to calculate electrodeamplitudes/configurations based on electrode and spinal geometry aspreviously described, and then time domain targeting may be used toscale the total current delivered through an electrode or group ofelectrodes corresponding to specific waveform neural target according tovalues of the applicable strength duration curve. FIG. 31 illustrates anon-limiting example for using time domain targeting. A target pole maybe programmed using two leads 3195 and 3196 which may be staggered leadsas illustrated. The anodic current and the cathodic current are splitequally in the illustrated, such that each lead has 50% of the anodiccurrent and 50% of the cathodic current. More particularly, the anodiccontribution of each lead may use a first anodic electrode and a secondanodic electrode, and the cathodic contribution of each lead may use afirst cathodic electrode and a second cathodic electrode. Even moreparticularly, the illustrated example indicates that the first anodicelectrode for each lead contributes 17% of the anodic current, thesecond anodic electrode for each lead contributes 33% of the anodiccurrent, the first cathodic electrode for each lead contributes 17% ofthe cathodic current, and the second cathodic electrode for each leadcontributes 33% of the cathodic current. The amplitude of the currentcontributions may be 0.8 mA for the first anodic electrode for eachlead, 1.5 mA for the second anodic electrode for each lead, −0.8 mA forthe first cathodic electrode for each lead, and −1.5 for the secondcathodic electrode for each lead. It is noted that the leads may or maynot be offset, and that the anodic and cathodic electrode contributionsmay be balanced or unbalanced on the lead. The waveform delivered usingthe first group of electrodes (illustrated by way of example and notlimitation as being on the first lead 3195) may be a 1.2 kHz pulsedwaveform, and the waveform delivered using the second group ofelectrodes (illustrated by way of example and not limitation as being onthe first lead 3195) may be a 1.2 kHz sinusoidal wave with a 25% dutycycle. Based on an apriori simulation or based on a modeled analyticrelationship of the waveform to threshold of the neural target, it maybe determined that the neural target for the second group of electrodeshas a strength duration threshold for the sinusoidal waveform has arelationship to the strength-duration threshold of the first group ofelectrodes for the pulsed waveform. In the simplified exampleillustrated in FIG. 31, the relationship is that the neural target forthe second group of electrodes has a strength duration threshold for thesinusoidal waveform is twice the strength-duration threshold of thefirst group of electrodes for the pulsed waveform. Thus, themultiplication factor for the time domain targeting is 1× of theamplitude of the current contribution for the first group of electrodesand 2× of the amplitude of the current contribution for the second groupof electrodes. The ratio of the current contributions for the first andsecond leads changes from 1:1 for the ideal target pole to 1:2 for thescaled real configuration. The amplitude of the current contributionsfor the first group of electrodes remains the same: 0.8 mA for the firstanodic electrode, 1.5 mA for the second anodic electrode, −0.8 mA forthe first cathodic electrode, and −1.5 for the second cathodicelectrode. However, the amplitude of the current contributions for thefirst group of electrodes is doubled: 1.6 mA for the first anodicelectrode, 3.0 mA for the second anodic electrode, −1.6 mA for the firstcathodic electrode, and −3.0 for the second cathodic electrode.Fractionalizations are adjusted according to scaled current/totalcurrent. The total of the fractionalizations add up to 100%. In theillustrated embodiments, the percentages do not include decimals, sorounding may cause the fractionalized percentage of the second lead tobe slightly different from twice the percentage of the first lead. Giventhe 1:2 ratio of the current contributions for the first and secondleads, the first anodic electrode for first lead contributes 12% of theanodic current, the first anodic electrode for second lead contributes23% of the anodic current, the second anodic electrode for the firstlead contributes 22% of the anodic current, the second anodic electrodefor the second lead contributes 43% of the anodic current, the firstcathodic electrode for first lead contributes 12% of the cathodiccurrent, the first cathodic electrode for second lead contributes 23% ofthe cathodic current, the second cathodic electrode for the first leadcontributes 22% of the cathodic current, the second cathodic electrodefor the second lead contributes 43% of the cathodic current. It is notedthat, rather than calculating the current value at each contact and thenthe fractionalization values using the current values, the programmingmay be performed by first determining the fractionalization values ateach contact, and then the current values using the fractionalizationvalues.

Space Domain and Time Domain Scaling

Various embodiments of the present subject matter allow for both spacedomain and time domain scaling. Some embodiments enable a user-selectedweighting for spatial versus temporal fractionalization adjustments. Theweighing may be limited to selection of preprogrammed weight or may beat the discretion of the user. For example, a user interface may includea feature such as a slider or dial used to define transitions betweenspatial and temporal scaling.

In FIG. 32A, the anodic current and the cathodic current are splitequally in the illustrated, such that each lead has 50% of the anodiccurrent and 50% of the cathodic current. More particularly, the anodiccontribution of each lead may use a first anodic electrode and a secondanodic electrode, and the cathodic contribution of each lead may use afirst cathodic electrode and a second cathodic electrode. Even moreparticularly, the illustrated example indicates that the first anodicelectrode for each lead contributes 17% of the anodic current, thesecond anodic electrode for each lead contributes 33% of the anodiccurrent, the first cathodic electrode for each lead contributes 17% ofthe cathodic current, and the second cathodic electrode for each leadcontributes 33% of the cathodic current. The amplitude of the currentcontributions may be 0.5 mA for the first anodic electrode for eachlead, 1 mA for the second anodic electrode for each lead, −0.5 mA forthe first cathodic electrode for each lead, and −1 mA for the secondcathodic electrode for each lead. It is noted that the leads may or maynot be offset, and that the anodic and cathodic electrode contributionsmay be balanced or unbalanced on the lead.

FIG. 32B illustrates a space domain scaling, which increases the currentcontribution of each electrode contact by 50%, such that with roundingto the nearest 0.1 mA, the amplitude of the current contributions may be0.8 mA for the first anodic electrode for each lead, 1.5 mA for thesecond anodic electrode for each lead, −0.8 mA for the first cathodicelectrode for each lead, and −1.5 mA for the second cathodic electrodefor each lead. The illustrated space domain scaling is weighted at 100%.It is noted that the space domain scaling could be weighted differently.For example, if weighted at 50%, the increased current contribution ateach electrode would only be 25%.

FIG. 32C illustrates 50% time domain scaling at 50%, and FIG. 32Dillustrates 100% time domain scaling. The stimulation threshold for theneural target of Group 2 is twice the threshold of the neural target forGroup 1. Therefore, for the 50% time domain scaling illustrated in FIG.32C, the amplitudes of current contribution of each contact may be 150%of the spatial only current contributions. For the 100% time domainscaling illustrated in FIG. 32D, the amplitudes of current contributionof each contact may be 200% of the spatial only current contributions.It is noted that the time domain scaling may be performed first,followed by the space domain scaling.

The transition between spatial and temporal could be linear (asillustrated by the 50% and 100% temporal scaling in FIG. 32C and FIG.32D), quadratic, or any other monotonic polynomial, exponential, orother relationship. The transitions may also vary according to originaltarget pole (left) rather than and/or in addition to a target pole thataccounts for space domain factors.

FIG. 33 illustrates an example of a system, with similarities to systemsillustrated in FIGS. 2-6, which may include one or more external devices3301 and at least one modulation device 3302. The system providesadditional detail to illustrate components that may be configured toperform various functions described above. The modulation device 3302may include an external modulation device or an implantable modulationdevice such as an implantable SCS device. The illustrated modulationdevice 3302 may include a modulation control circuit 3303 and amodulation output circuit 3304. Storage (e.g. memory) 3305 may includeprogrammed parameter sets 3306, including parameter sets determinedusing space domain scaling and/or time domain scaling. The modulationcontrol circuitry 3303 may be configured to use the programmed parametersets to control the modulation output circuit to allocate the energy tothe electrodes to provide the desired modulation field. In someembodiments, the modulation device may include sensor circuitry 3307,including or configured to interface with one or more sensors, which maybe used to provide an object feedback measure to the neuromodulation.Examples of such measures may include, but are not limited to, ECAPs andLFPs. The external device 3301 may include programming control circuitry3308, storage 3309, and a user interface 3310 such as a graphical userinterface (GUI). The programming control circuitry 3308 may use data andinstructions stored in the storage 3309 to program the modulation device3302 with the parameters sets. Some embodiments, the external device(s)may include sensor circuitry 3311, including one or more sensors, whichmay be used to provide an object feedback measure to theneuromodulation. Examples of such measures may include, but are notlimited to, ECAPs and LFPs. The GUI 3310 may include an interface toreceive subjective feedback from the patient, clinician or other user.The GUI 3310 may also include other control and display elements toassist with the programming of the modulation device with the parametersets.

The illustrated programming control circuitry 3308 includes circuitry3312 configured to program ideal target pole(s) and/or target modulationfields. Some embodiments may further include circuitry 3313 configuredfor use in selecting the electrode groups (e.g. monopolar, bipolar,tripolar or other multipolar arrangement) to be used in the calibrationprocess. Calibration routine circuitry 3314, and scaling circuitry 3315may be incorporated only into the external device(s), only into themodulation device, or distributed between or among the externaldevice(s) and the modulation device. The calibration routine circuitrycontrols the calibration of the different electrode groups to measurefeedback and provide the feedback metric used to scale the allocatedenergy used to provide the ideal target pole. For example, a calibrationroutine may be configured to test different combinations if electrodesin a bipole arrangement to provide a feedback metric for each bipolearrangement. The scaling circuitry may be configured to performfunctions described above to determine and apply the space domainscaling factor and/or the time domain scaling factor to the allocatedenergy.

It is noted that a circuit or circuitry may be implemented as part of amicroprocessor circuit, which may be a dedicated processor such as adigital signal processor, application specific integrated circuit(ASIC), microprocessor, or other type of processor for processinginformation including physical activity information. The microprocessorcircuit may be a general purpose processor that may receive and executea set of instructions of performing the functions, methods, ortechniques described herein. The circuit or circuitry may be implementedas one or more other circuits or sub-circuits that may, alone or incombination, perform the functions, methods or techniques describedherein. In an example, hardware of the circuit set may be immutablydesigned to carry out a specific operation (e.g., hardwired). In anexample, the hardware of the circuit set may include variably connectedphysical components (e.g., execution units, transistors, simplecircuits, etc.) including a computer readable medium physically modifiedto encode instructions of the specific operation. Instructions mayenable embedded hardware (e.g., the execution units or a loadingmechanism) to create members of the circuit set in hardware via variableconnections to carry out portions of the specific operation when inoperation. Accordingly, the computer readable medium is communicativelycoupled to the other components of the circuit set member when thedevice is operating. In an example, any of the physical components maybe used in more than one member of more than one circuit set. Forexample, under operation, execution units may be used in a first circuitof a first circuit set at one point in time and reused by a secondcircuit in the first circuit set, or by a third circuit in a secondcircuit set at a different time.

The terms “tangible” and “non-transitory,” as used herein, are intendedto describe a machine-readable storage medium such as acomputer-readable storage medium (or “memory”) excluding propagatingelectromagnetic signals, but are not intended to otherwise limit thetype of physical computer-readable storage device that is encompassed bythe phrase computer-readable medium or memory. By way of example and notlimitation, a machine may include a modulation device or a programmingdevice such as a remote control or clinician programmer. For instance,the terms “non-transitory computer readable medium” or “tangible memory”are intended to encompass types of storage devices that do notnecessarily store information permanently, including for example, randomaccess memory (RAM).

The term “machine readable medium” may include a single medium ormultiple media (e.g., a centralized or distributed database, and/orassociated caches and servers) configured to store instructions, andincludes any medium that is capable of storing, encoding, or carryinginstructions for execution by the machine and that cause the machine toperform any one or more of the techniques of the present disclosure, orthat is capable of storing, encoding or carrying data structures used byor associated with such instructions. Non-limiting machine readablemedium examples may include solid-state memories, and optical andmagnetic media. In an example, a machine readable medium include:nonvolatile memory, such as semiconductor memory devices (e.g.,Electrically Programmable Read-Only Memory (EPROM), ElectricallyErasable Programmable Read-Only Memory (EEPROM)) and flash memorydevices; magnetic disks, such as internal hard disks and removabledisks; magneto-optical disks; and CD-ROM and DVD-ROM disks. Programinstructions and data stored on a tangible computer-accessible storagemedium in non-transitory form may further be transmitted by transmissionmedia or signals such as electrical, electromagnetic, or digitalsignals, which may be conveyed via a communication medium such as anetwork and/or a wireless link.

Method examples described herein can be machine or computer-implementedat least in part. Some examples may include a computer-readable mediumor machine-readable medium encoded with instructions operable toconfigure an electronic device or system to perform methods as describedin the above examples. An implementation of such methods can includecode, such as microcode, assembly language code, a higher-level languagecode, or the like. Such code can include computer readable instructionsfor performing various methods. The code can form portions of computerprogram products. Further, the code can be tangibly stored on one ormore volatile or non-volatile computer-readable media during executionor at other times.

Various embodiments are illustrated in the figures above. One or morefeatures from one or more of these embodiments may be combined to formother embodiments.

The above detailed description is intended to be illustrative, and notrestrictive. The scope of the disclosure should, therefore, bedetermined with references to the appended claims, along with the fullscope of equivalents to which such claims are entitled.

The above detailed description is intended to be illustrative, and notrestrictive. The scope of the disclosure should, therefore, bedetermined with references to the appended claims, along with the fullscope of equivalents to which such claims are entitled.

What is claimed is:
 1. A method, comprising: determining target energyallocations for a plurality of electrodes based on at least one targetpole to provide a target sub-perception modulation field; andnormalizing the target sub-perception modulation field, includingdetermining a time domain scaling factor to account for at least oneproperty of a neural target or of a neuromodulation waveform, andapplying the time domain scaling factor to the target energyallocations.
 2. The method of claim 1, wherein the determining the timedomain scaling factor includes determining the time domain scalingfactor based on a type of neural structure.
 3. The method of claim 1,wherein the determining the time domain scaling factor includesdetermining the time domain scaling factor based on at least one neuralstructure property, the at least one neural structure property includinga geometrical property or an electrical property.
 4. The method of claim1, wherein the determining the time domain scaling factor includesdetermining the time domain scaling factor based on a pulse width of theneuromodulation waveform.
 5. The method of claim 1, wherein thedetermining the time domain scaling factor includes determining the timedomain scaling factor based on a frequency of the neuromodulationwaveform.
 6. The method of claim 1, wherein the determining the timedomain scaling factor includes determining the time domain scalingfactor based on a duty cycle of the neuromodulation waveform.
 7. Themethod of claim 1, wherein the determining the time domain scalingfactor includes determining the time domain scaling factor based on ashape or pattern of the neuromodulation waveform.
 8. The method of claim1, wherein the determining the time domain scaling factor includesdetermining the time domain scaling factor based on a type of theneuromodulation waveform.
 9. The method of claim 1, wherein thenormalizing the target sub-perception modulation field includesdetermining the time domain scaling factor to account for at least oneproperty of the neural target and for at least one property of theneuromodulation waveform.
 10. The method of claim 1, wherein thenormalizing the target sub-perception modulation field includesdetermining the time domain scaling factor to account for at a firstproperty and a second property selected from the group consisting of: atype of neural structure; at least one neural structure property, the atleast one neural structure property including a geometrical property oran electrical property; and a neuromodulation waveform property.
 11. Themethod of claim 10, wherein the determining the time domain scalingfactor to account for at the first property and the second propertyincludes determining a first time domain scaling factor to account forthe first property, determining a second time domain scaling factor toaccount for the second property, and multiplying the first time domainscaling factor and the second time domain scaling factor.
 12. The methodof claim 1, further comprising calibrating a plurality of electrodegroups in the plurality of electrodes where each of the plurality ofelectrode groups have an electrode configuration and include anelectrode set of at least one electrode from the plurality ofelectrodes, wherein the calibrating the electrode groups includes, foreach of the plurality of electrode groups, delivering modulation energyto a neural target and receiving feedback; and determining a spacescaling factor using the feedback to account for actual relativepositions between the electrode groups and the neural target, andfurther applying the space domain scaling factor to the target energyallocations.
 13. The method of claim 1, wherein the determining the timedomain scaling factor includes retrieving the time domain scaling factorfrom a lookup table.
 14. The method of claim 1, wherein the determiningthe time domain scaling factor includes calculating the time domainscaling factor from a modeled analytic relationship between a thresholdof the neural target and the at least one property of the neural targetor of the neuromodulation waveform.
 15. A system to program aneuromodulator to deliver neuromodulation to a neural target using aplurality of electrodes, the system comprising a programming controlcircuit configured to: determine target energy allocations for theplurality of electrodes based on at least one target pole to provide atarget sub-perception modulation field; and normalize the targetsub-perception modulation field, including determine a time domainscaling factor to account for at least one property of a neural targetor of a neuromodulation waveform, and apply the time domain scalingfactor to the target energy allocations.
 16. The system of claim 15,further comprising an external device that includes the programmingcontrol circuit and a user interface, wherein the external device isconfigured to program parameter sets into an implantable modulationdevice.
 17. The system of claim 16, wherein the programming controlcircuit is configured to determine the time domain scaling factor toaccount for at least one property of the neural target and to accountfor at least one property of the neuromodulation waveform.
 18. Anon-transient machine readable medium containing program instructionsfor causing a machine to: determine target energy allocations for aplurality of electrodes based on at least one target pole to provide atarget sub-perception modulation field; and normalize the targetsub-perception modulation field, including determining a time domainscaling factor to account for at least one property of a neural targetor of a neuromodulation waveform, and applying the time domain scalingfactor to the target energy allocations.
 19. The non-transient machinereadable medium of claim 18, wherein the normalizing the targetsub-perception modulation field includes determining the time domainscaling factor to account for at least a first property selected fromthe group consisting of: a type of neural structure; at least one neuralstructure property, the at least one neural structure property includinga geometrical property or an electrical property; and a neuromodulationwaveform property.
 20. The non-transient machine readable medium ofclaim 19, wherein the normalizing the target sub-perception modulationfield includes determining the time domain scaling factor to account forat least a second property selected from the group consisting of: thetype of neural structure; the at least one neural structure property;and a neuromodulation waveform property.